Object Surface

Object surface research focuses on understanding and characterizing the properties and features of surfaces, with key objectives including defect detection, material property prediction, and accurate surface reconstruction. Current research heavily utilizes machine learning, particularly deep learning models like Vision Transformers, convolutional neural networks, and diffusion models, alongside more traditional statistical and geometric methods, to analyze diverse surface types ranging from industrial metals and wood to complex 3D shapes and even planetary surfaces. These advancements have significant implications for various fields, improving manufacturing efficiency through automated inspection, enhancing robotic manipulation through tactile sensing, and advancing our understanding of planetary science and materials science through improved modeling and prediction capabilities.